Analysis of Positioning Uncertainty in Cooperative Localization and Target Tracking (CLATT)

نویسندگان

  • Faraz M. Mirzaei
  • Anastasios I. Mourikis
  • Stergios I. Roumeliotis
چکیده

In this report, we study the positioning accuracy of Cooperative Localization and Target Tracking (CLATT) in a network of mobile robots, and derive analytical upper bounds for the positioning uncertainty. The obtained bounds provide a description for the asymptotic positioning performance of the robots and the targets as a function of the sensor characteristics, and the structure of the graph of relative position measurements. By employing an Extended Kalman Filter (EKF) formulation for data fusion, two expressions are derived for the asymptotic positioning performance. One expression provides the guaranteed worst-case positioning accuracy, whereas the other determines an upper bound on the expected position estimates’ covariance. We investigate the effects of jointly estimating the targets’ and the robots’ position, and demonstrate that it results in better accuracy for the robots’ position estimates.

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تاریخ انتشار 2005